1. Technical Field
The present invention relates to mobile devices, and more particularly to distributed artificial intelligence services on a cell phone.
2. Description of the Related Art
Mobile device development has been driven by more and more sophisticated needs. Many of these potential applications, such as object/text recognition, speech recognition, semantic analysis and machine translation, depend heavily on machine intelligence, which is often achieved by machine learning techniques.
Unfortunately, many machine learning algorithms have large computing or storage requirements which make them less tractable for mobile devices. A straightforward idea is to gather data on the device and send the data to powerful servers for processing.
Thus, in most cases, the user selects an application appropriate for processing the kind of input data they will provide. Then the complete input data is sent by that application to a predetermined server for processing. In most cases, a static image is taken from the camera and the whole image is sent to the server for processing.
For example, a Bar Code application will process whole input images that include bar codes and send the result off for analysis by a server. For an object identification application, a complete image may be taken by the camera and sent to a server for analysis.
However, the network bandwidth could be a bottleneck in such scenarios. Hence, a good workload balance scheme between the handheld devices and the servers in the cloud will be very valuable.